A novel fast phase correlation algorithm for peak wavelength detection of fiber Bragg gratings sensors

Alfredo Lamberti, Steve Vanlanduit, Ben De Pauw, Francis Berghmans

Research output: Contribution to journalArticle

56 Citations (Scopus)
159 Downloads (Pure)


Fiber Bragg Gratings (FBGs) can be used as sensors for strain, temperature and pressure measurements. For this purpose, the ability to determine the Bragg peak wavelength with adequate wavelength resolution and accuracy is essential. However, conventional peak detection techniques, such as the maximum detection algorithm, can yield inaccurate and imprecise results, especially when the Signal to Noise Ratio (SNR) and the wavelength resolution are poor. Other techniques, such as the cross-correlation demodulation algorithm are more precise and accurate but require a considerable higher computational effort. To overcome these problems, we developed a novel fast phase correlation (FPC) peak detection algorithm, which computes the wavelength shift in the reflected spectrum of a FBG sensor. This paper analyzes the performance of the FPC algorithm for different values of the SNR and wavelength resolution. Using simulations and experiments, we compared the FPC with the maximum detection and cross-correlation algorithms. The FPC method demonstrated a detection precision and accuracy comparable with those of cross-correlation demodulation and considerably higher than those obtained with the maximum detection technique. Additionally, FPC showed to be about 50 times faster than the cross-correlation. It is therefore a promising tool for future implementation in real-time systems or in embedded hardware intended for FBG sensor interrogation. (C) 2014 Optical Society of America
Original languageEnglish
Pages (from-to)7099-7112
Number of pages14
JournalOpt. Express
Publication statusPublished - 2014



Fingerprint Dive into the research topics of 'A novel fast phase correlation algorithm for peak wavelength detection of fiber Bragg gratings sensors'. Together they form a unique fingerprint.

Cite this